Young technology firms’ sluggish growth rate is a troubling sign for the US economy, according to a newly-released white paper from the Kauffman Foundation, a nonprofit organization that studies entrepreneurship and provides grants to award educational achievement and entrepreneurial success. The high-tech sector has traditionally sparked economic growth in recent decades. However, the Kauffman report finds the number of technology firms five years old and younger—which typically drive job creation—has fallen from a high of 113,000 in 2001 to about 80,000 now, as it was in the mid-1990s. One factor that may have skewed the number is the acquisition of young firms by established technology companies. The report also finds that technology firms’ job reallocation rate—which basically subtracts the rate at which jobs are lost from the rate at which they are created—has fallen to the lowest rate since the late 1970s “Because young high-tech firms are so disproportionately important for innovation and job creation, a slowdown in this sector calls for a new approach to fostering a stronger entrepreneurial economy,” said Dane Stangler, the Kauffman Foundation’s vice president of research and policy. (Reuters)(Ewing Marion Kauffman Foundation)
Wednesday, March 5, 2014
Friday, November 2, 2012
A Travelling Salesman Problem special case: 30-year-old problem solved
The Travelling Salesman Problem, or TSP, was first defined around 150 years ago. The problem then was to find the shortest possible route for salesmen to visit each of their customers once and finish back where they started. In the 21st century, this same problem now applies to a multitude of activities -- delivering fresh stock to supermarkets, supplying manufacturing lines, air traffic control, and even DNA sequencing. Complex and sophisticated computer programmes using optimisation -- where algorithms produce the best possible result from multiple choices -- now form the basis of solutions to these modern-day problems. The time required to find an optimal solution is vital for practical application of the TSP. How long can lorry drivers wait for their route to be finalised when the salads they hope to deliver will only be fresh for another 24 hours? How long can air traffic control keep an airliner flying in circles around Heathrow Airport?
The theoretical background behind these types of questions is studied in the theory of computational complexity. The TSP is of paramount significance for this branch of knowledge. Even a small incremental step in understanding the nature of this problem is of interest and benefit to the scientific community.
Associate Professor Dr Vladimir Deineko of Warwick Business School, together with Eranda Cela (University of Technology Graz, Austria) and Gerhard Woeginger (Eindhoven University, the Netherlands) have addressed a special case of the TSP, or open problem as it is termed, first identified 30 years ago. Dr Deineko's and his colleagues' work gives a solution of theoretical significance for computer science and operational research.
Dr Deineko comments, "The TSP has served as a benchmark problem for all new and significant approaches developed in optimisation. It belongs to the set of so called NP-hard problems. There are obviously some special cases when the TSP can be solved efficiently. The simplest possible case is when the cities are the points on a straight line and the distances are as-the-crow-flies-distances. One can easily get the shortest route for visiting all the points in this case. Probably the next simplest case would be the case when the cities are the points on two perpendicular lines and the distances are again as-the-crow-flies-distances (so-called X-and-Y-axes TSP).
"Despite its apparent simplicity, this special case problem has been circulating in the scientific community for around 30 years. Until our work, it was not known whether an algorithm existed which would guarantee finding an optimal solution to any instance of these problems within a reasonable amount of time. We have now proved that the X-and-Y axes TSP can be easily solved in a number of steps proportional to the square of the number of cities."
Dean of WBS, Professor Mark Taylor, comments, "I congratulate Dr Deineko and his colleagues in advancing our knowledge of this enormously complex subject. They have produced cutting-edge research which is not only of great importance to the scientific community, but ultimately also of great relevance to all of us who depend on modern technology as we go about our daily lives."
Share this story on Facebook, Twitter, and Google:Other social bookmarking and sharing tools:
Story Source:
The above story is reprinted from materials provided by University of Warwick, via AlphaGalileo.
Note: Materials may be edited for content and length. For further information, please contact the source cited above.
Journal Reference:
Eranda Çela, Vladimir Deineko, Gerhard J. Woeginger. The x-and-y-axes travelling salesman problem. European Journal of Operational Research, 2012; 223 (2): 333 DOI: 10.1016/j.ejor.2012.06.036Note: If no author is given, the source is cited instead.
Disclaimer: Views expressed in this article do not necessarily reflect those of ScienceDaily or its staff.
